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| #!/usr/bin/env python3 | |
| """ | |
| Debug Task3 optimal reward | |
| """ | |
| import os | |
| import sys | |
| import random | |
| sys.path.insert(0, os.path.join(os.path.dirname(__file__), "server")) | |
| from environment import EmailEnv | |
| from models import Action | |
| def debug_task3(): | |
| env = EmailEnv() | |
| env.reset(task="task3", seed=42) | |
| print(f"Initial inbox: {len(env.inbox)} emails") | |
| for i, email in enumerate(env.inbox): | |
| print( | |
| f" {i + 1}. {email['id']}: type={email['type']}, urgency={email['urgency']}, sentiment={email['sentiment']}, spam_score={email['spam_score']}" | |
| ) | |
| step = 0 | |
| total_reward = 0.0 | |
| while step < 20 and env.inbox: | |
| # Process all emails optimally | |
| for email in env.inbox[:]: | |
| is_spam = email.get("type") == "SPAM" or email.get("ground_truth", 0) == 1 | |
| if is_spam: | |
| action_type = "delete" | |
| else: | |
| urgency = email.get("urgency", "MEDIUM") | |
| sentiment = email.get("sentiment", "Professional") | |
| if urgency == "HIGH" or sentiment == "Aggressive": | |
| action_type = "escalate" | |
| else: | |
| action_type = "open" | |
| action = Action(action_type=action_type, email_id=email["id"]) | |
| obs = env.step(action) | |
| total_reward += obs.reward | |
| if obs.done: | |
| break | |
| step += 1 | |
| print(f"\nAfter {step} steps:") | |
| print(f" total_reward = {total_reward:.4f}") | |
| print(f" processed_emails = {env.processed_emails}") | |
| print(f" initial_email_count = {env.initial_email_count}") | |
| print(f" inbox remaining = {len(env.inbox)}") | |
| score = env.grader() | |
| print(f" grader score = {score:.4f}") | |
| if __name__ == "__main__": | |
| random.seed(42) | |
| debug_task3() | |